"""
 Copyright (C) 2018-2020 Intel Corporation

 Licensed under the Apache License, Version 2.0 (the "License");
 you may not use this file except in compliance with the License.
 You may obtain a copy of the License at

      http://www.apache.org/licenses/LICENSE-2.0

 Unless required by applicable law or agreed to in writing, software
 distributed under the License is distributed on an "AS IS" BASIS,
 WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
 See the License for the specific language governing permissions and
 limitations under the License.
"""

import unittest

import numpy as np
from generator import generator, generate

from mo.front.extractor import input_user_data_repack, output_user_data_repack, update_ie_fields, add_input_op, \
    get_node_id_with_ports
from mo.front.extractor import spatial_attr_getter, add_input_ops, attr_getter, CaffePythonFrontExtractorOp, \
    add_output_ops
from mo.graph.graph import Node
from mo.utils.error import Error
from mo.utils.ir_engine.compare_graphs import compare_graphs
from mo.utils.unittest.extractors import FakeMultiParam
from mo.utils.unittest.graph import build_graph, build_graph_with_edge_attrs, build_graph_with_attrs


class FakePythonParam:
    def __init__(self, param: FakeMultiParam):
        self.__setattr__('python_param', param)


nodes_attributes = {'input': {'kind': 'data'},
                    'pool_1': {'type': 'Pooling', 'kind': 'op'},
                    'output': {'kind': 'data'},
                    'op_output': {'kind': 'op', 'op': 'Result'},
                    }


class UpdateIEFieldsTest(unittest.TestCase):
    def test_default_update_ie_fields(self):
        update_ie_fields({}, ir_version=None)

    def test_not_set_update_ie_fields(self):
        with self.assertRaisesRegex(Error, 'Unrecognized IR version.*'):
            update_ie_fields({}, ir_version='abracadabra')


class TestExtractor(unittest.TestCase):
    def test_spatial_attr_getter(self):
        input_shape = np.array([1, 125, 13, 13])
        params = {
            'kernel': np.array([1, 1, 1, 2]),
            'pad': np.array([1, 1, 3, 4]),
            'stride': np.array([1, 1, 2, 3]),
        }
        graph = build_graph(nodes_attributes,
                            [('input', 'pool_1'),
                             ('pool_1', 'output'),
                             ('output', 'op_output')
                             ],
                            {'input': {'shape': input_shape},
                             'pool_1': {**params, 'spatial_dims': [2, 3]},
                             'output': {'shape': None}})
        pool_1_node = Node(graph, 'pool_1')
        for param in params.keys():
            if type(params[param]) is np.ndarray:
                port_lambda = lambda x: x
                self.assertEqual(params[param][2],
                                 spatial_attr_getter(pool_1_node, field=param, dim=0, post=port_lambda))
                self.assertEqual(params[param][3],
                                 spatial_attr_getter(pool_1_node, field=param, dim=1, post=port_lambda))

    def test_attr_getter(self):
        nodes = {'input': {'kind': 'data'},
                 'reshape': {'type': 'Reshape', 'kind': 'op'},
                 'output': {'kind': 'data'},
                 'op_output': {'type': 'Result', 'kind': 'op'},
                 }
        input_shape = np.array([1, 125, 13, 13])
        params = {
            'dim': [1, 1, 2, 3],
            'max_size': np.array([3, 2, 1, 0])
        }
        expect_params = {
            'dim': "1,1,2,3",
            'max_size': "3,2,1,0",
        }
        graph = build_graph(nodes,
                            [('input', 'reshape'),
                             ('reshape', 'output'),
                             ('output', 'op_output')
                             ],
                            {'input': {'shape': input_shape},
                             'reshape': {**params, 'spatial_dims': [2, 3]},
                             'output': {'shape': None}})
        pool_1_node = Node(graph, 'reshape')
        for param in params.keys():
            if type(params[param]) is list:
                self.assertEqual(expect_params[param],
                                 attr_getter(pool_1_node, param))


class TestAddInputOp(unittest.TestCase):
    nodes = [
        ('op_node', {'kind': 'op'}),
        ('future_input', {'kind': 'op'}),
        ('another_node', {'kind': 'op'}),
    ]
    edges = [('future_input', 'op_node', {'in': 1, 'out': 0}),
             ('another_node', 'op_node', {'in': 0, 'out': 0})]

    def test_in_port_no_data(self):
        graph = build_graph_with_attrs(nodes_with_attrs=self.nodes, edges_with_attrs=self.edges)
        new_input_shape = np.array([1, 2, 3, 4])
        graph_ref = build_graph_with_attrs(nodes_with_attrs=self.nodes, edges_with_attrs=self.edges[1:],
                                           new_nodes_with_attrs=[('input_node', {'kind': 'op', 'op': 'Parameter',
                                                                                 'shape': new_input_shape})],
                                           new_edges_with_attrs=[('input_node', 'op_node', {'in': 1, 'out': 0})])
        add_input_op(graph, 'op_node', 1, data=False, shape=new_input_shape)
        graph.remove_edge('future_input', 'op_node')
        (flag, resp) = compare_graphs(graph, graph_ref, last_node='op_node')
        self.assertTrue(flag, resp)

    def test_in_port_with_data(self):
        graph = build_graph_with_attrs(nodes_with_attrs=self.nodes, edges_with_attrs=self.edges)
        new_input_shape = np.array([1, 2, 3, 4])
        graph_ref = build_graph_with_attrs(nodes_with_attrs=self.nodes, edges_with_attrs=self.edges[1:],
                                           new_nodes_with_attrs=[('input_node', {'kind': 'op', 'op': 'Parameter',
                                                                                 'shape': new_input_shape}),
                                                                 ('input_data', {'kind': 'data'})],
                                           new_edges_with_attrs=[('input_node', 'input_data', {'in': 0, 'out': 0}),
                                                                 ('input_data', 'op_node', {'in': 1, 'out': 0})])
        add_input_op(graph, 'op_node', 1, data=True, shape=new_input_shape)
        graph.remove_edge('future_input', 'op_node')
        (flag, resp) = compare_graphs(graph, graph_ref, last_node='op_node')
        self.assertTrue(flag, resp)

    nodes_out = [
        ('op_node', {'kind': 'op'}),
        ('future_input', {'kind': 'op'}),
        ('another_node', {'kind': 'op'}),
    ]
    edges_out = [('op_node', 'future_input', {'in': 0, 'out': 1}),
                 ('op_node', 'another_node', {'in': 0, 'out': 0})]

    def test_out_port_no_data(self):
        graph = build_graph_with_attrs(nodes_with_attrs=self.nodes_out, edges_with_attrs=self.edges_out)
        new_input_shape = np.array([1, 2, 3, 4])
        graph_ref = build_graph_with_attrs(nodes_with_attrs=self.nodes_out, edges_with_attrs=self.edges_out[1:],
                                           new_nodes_with_attrs=[('input_node', {'kind': 'op', 'op': 'Parameter',
                                                                                 'shape': new_input_shape})],
                                           new_edges_with_attrs=[('input_node', 'future_input', {'in': 0, 'out': 0})])
        add_input_op(graph, 'op_node', 1, data=False, shape=new_input_shape, is_out_port=True)
        graph.remove_edge('op_node', 'future_input')
        (flag, resp) = compare_graphs(graph, graph_ref, last_node='another_node')
        self.assertTrue(flag, resp)
        (flag, resp) = compare_graphs(graph, graph_ref, last_node='future_input')
        self.assertTrue(flag, resp)

    def test_out_port_with_data(self):
        graph = build_graph_with_attrs(nodes_with_attrs=self.nodes_out, edges_with_attrs=self.edges_out[1:],
                                       new_nodes_with_attrs=[('input_data', {'kind': 'data', 'shape': None, 'value': None})],
                                       new_edges_with_attrs=[('op_node', 'input_data', {'out': 1, 'in': 0}),
                                                             ('input_data', 'future_input', {'in': 0, 'out': 0})])
        new_input_shape = np.array([1, 2, 3, 4])
        graph_ref = build_graph_with_attrs(nodes_with_attrs=self.nodes_out, edges_with_attrs=self.edges_out[1:],
                                           new_nodes_with_attrs=[('input_node', {'kind': 'op', 'op': 'Parameter',
                                                                                 'shape': new_input_shape}),
                                                                 ('input_data', {'kind': 'data', 'shape': None})],
                                           new_edges_with_attrs=[('input_node', 'input_data', {'in': 0, 'out': 0}),
                                                                 ('input_data', 'future_input', {'in': 0, 'out': 0})])
        add_input_op(graph, 'op_node', 1, data=True, shape=new_input_shape, is_out_port=True)
        graph.remove_edge('op_node', 'input_data')

        (flag, resp) = compare_graphs(graph, graph_ref, last_node='another_node')
        self.assertTrue(flag, resp)
        (flag, resp) = compare_graphs(graph, graph_ref, last_node='future_input')
        self.assertTrue(flag, resp)


class TestInputAddition(unittest.TestCase):
    # Tests for input
    nodes = {'node_1': {'type': 'Identity', 'kind': 'op', 'op': 'Parameter'},
             'conv_1': {'type': 'Convolution', 'kind': 'op', 'op': 'NotPlaceholder'},
             'relu_1': {'type': 'ReLU', 'kind': 'op', 'op': 'NotPlaceholder'},
             }
    edges = [
        ('node_1', 'conv_1'),
        ('conv_1', 'relu_1'),
    ]

    def test_none_out_port_raise(self):
        graph = build_graph(self.nodes, self.edges)
        shape = np.array([1, 2, 3, 4])
        inputs = {'conv_1': [{'shape': shape, 'out': None}]}
        with self.assertRaisesRegex(Error, 'Output port for input node conv_1 should be specified, it cannot be None!'):
            add_input_ops(graph=graph, user_defined_inputs=inputs, before_infer=True)

    def test_wrong_output_port_raise(self):
        graph = build_graph(self.nodes, self.edges)
        shape = np.array([1, 2, 3, 4])
        inputs = {'conv_1': [{'shape': shape, 'out': 5}]}
        with self.assertRaisesRegex(Error, 'Output port index 5 is out of number of available output ports for node'):
            add_input_ops(graph=graph, user_defined_inputs=inputs, before_infer=True)

    def test_wrong_input_port_raise(self):
        graph = build_graph(self.nodes, self.edges)
        shape = np.array([1, 2, 3, 4])
        inputs = {'conv_1': [{'shape': shape, 'in': 5}]}
        with self.assertRaisesRegex(Error, 'Input port index 5 is out of number of available input ports for node'):
            add_input_ops(graph=graph, user_defined_inputs=inputs, before_infer=True)

    def test_one_input_one_shape(self):
        shape = np.array([1, 2, 3, 4])
        inputs = {'conv_1': [{'shape': shape}]}
        nodes = {
            'old_input': {'type': 'Identity', 'kind': 'op', 'op': 'Parameter'},
            'conv_1': {'type': 'Convolution', 'kind': 'op', 'op': 'NotPlaceholder'},
            'relu_1': {'type': 'ReLU', 'kind': 'op', 'op': 'NotPlaceholder'},
            'output': {'type': 'SoftMax', 'kind': 'op', 'op': 'NotPlaceholder'}
        }
        edges = [
            ('old_input', 'conv_1'),
            ('conv_1', 'relu_1'),
            ('relu_1', 'output')
        ]
        graph = build_graph(nodes, edges)
        add_input_ops(graph=graph, user_defined_inputs=inputs, before_infer=True)
        new_input = list(graph.in_edges('conv_1'))[0][0]
        self.assertFalse(graph.node['old_input']['is_input'])
        self.assertTrue(graph.node[new_input]['is_input'])
        self.assertTrue((new_input, 'conv_1') in graph.edges())
        self.assertTrue(('old_input', 'conv_1') not in graph.edges())
        shapes_are_equal = np.array_equal(graph.node[new_input]['shape'], shape)
        self.assertTrue(shapes_are_equal)

    def test_one_input_no_shape(self):
        shape = None
        inputs = {'conv_1': [{'shape': shape}]}
        nodes = {
            'old_input': {'type': 'Parameter', 'kind': 'op', 'op': 'Parameter'},
            'old_input_data': {'kind': 'data', 'value': None, 'shape': np.array([-1, 224, 224, 3])},
            'conv_1': {'type': 'Convolution', 'kind': 'op', 'op': 'NotPlaceholder'},
            'conv_1_data': {'kind': 'data', 'value': True, 'shape': np.array([-1, 224, 224, 3])},
            'relu_1': {'type': 'ReLU', 'kind': 'op', 'op': 'NotPlaceholder'},
            'relu_1_data': {'kind': 'data', 'value': None, 'shape': np.array([-1, 112, 112, 64])},
            'output': {'type': 'SoftMax', 'kind': 'op', 'op': 'NotPlaceholder'},
            'output_data': {'name': 'output_data', 'kind': 'data', 'shape': np.array([-1, 112, 112, 64])},
            'op_output': {'kind': 'op', 'op': 'Result'}
        }
        edges = [
            ('old_input', 'old_input_data'),
            ('old_input_data', 'conv_1'),
            ('conv_1', 'conv_1_data'),
            ('conv_1_data', 'relu_1'),
            ('relu_1', 'relu_1_data'),
            ('relu_1_data', 'output'),
            ('output', 'output_data'),
            ('output_data', 'op_output')
        ]
        graph = build_graph(nodes, edges)
        add_input_ops(graph=graph, user_defined_inputs=inputs, before_infer=False)
        new_input = list(graph.in_edges(list(graph.in_edges('conv_1'))[0][0]))[0][0]
        new_input_data = list(graph.in_edges('conv_1'))[0][0]
        self.assertFalse(graph.node['old_input']['is_input'])
        self.assertTrue(graph.node[new_input]['is_input'])
        self.assertTrue((new_input_data, 'conv_1') in graph.edges())
        self.assertTrue(('old_input_data', 'conv_1') not in graph.edges())
        self.assertIsNotNone(graph.node[new_input_data]['shape'])

    def test_two_inputs_two_shapes_positive_1(self):
        shape_1 = [1, 2, 3, 4]
        shape_2 = [4, 3, 2, 1]
        inputs = {'node_1': [{'shape': shape_1}], 'node_4': [{'shape': shape_2}]}
        nodes = {
            'input_1': {'type': 'Identity', 'kind': 'op', 'op': 'Parameter'},
            'input_2': {'type': 'Identity', 'kind': 'op', 'op': 'Parameter'},
            'node_1': {'type': 'Identity', 'kind': 'op', 'op': 'NotPlaceholder'},
            'node_2': {'type': 'Identity', 'kind': 'op', 'op': 'NotPlaceholder'},
            'node_3': {'type': 'Identity', 'kind': 'op', 'op': 'NotPlaceholder'},
            'node_4': {'type': 'Identity', 'kind': 'op', 'op': 'NotPlaceholder'},
            'output': {'kind': 'op', 'op': 'Result'}
        }
        edges = [
            ('input_1', 'node_1'),
            ('node_1', 'node_2'),
            ('node_3', 'output'),
            ('input_2', 'node_4'),
            ('node_4', 'output')
        ]
        graph = build_graph(nodes, edges)
        add_input_ops(graph=graph, user_defined_inputs=inputs, before_infer=True)
        new_input_1 = list(graph.in_edges('node_1'))[0][0]
        new_input_2 = list(graph.in_edges('node_4'))[0][0]
        self.assertFalse(graph.node['input_1']['is_input'])
        self.assertTrue(graph.node[new_input_1]['is_input'])
        self.assertTrue(graph.node[new_input_2]['is_input'])
        self.assertTrue((new_input_1, 'node_1') in graph.edges())
        self.assertTrue((new_input_2, 'node_4') in graph.edges())
        self.assertListEqual(shape_1, graph.node[new_input_1]['shape'])
        self.assertListEqual(shape_2, graph.node[new_input_2]['shape'])

    def test_two_inputs_two_shapes_not_all_inputs(self):
        shape_1 = [1, 2, 3, 4]
        shape_2 = [4, 3, 2, 1]
        inputs = {'node_1': [{'shape': shape_1}], 'node_4': [{'shape': shape_2}]}
        nodes = {
            'input_1': {'type': 'Identity', 'kind': 'op', 'op': 'Parameter'},
            'input_2': {'type': 'Identity', 'kind': 'op', 'op': 'Parameter'},
            'node_1': {'type': 'Identity', 'kind': 'op', 'op': 'NotPlaceholder'},
            'node_2': {'type': 'Identity', 'kind': 'op', 'op': 'NotPlaceholder'},
            'node_3': {'type': 'Identity', 'kind': 'op', 'op': 'NotPlaceholder'},
            'node_4': {'type': 'Identity', 'kind': 'op', 'op': 'NotPlaceholder'},
            'output': { 'kind': 'op', 'op': 'Result'},
            'input_3': {'type': 'Identity', 'kind': 'op', 'op': 'Parameter'}
        }
        edges = [
            ('input_1', 'node_1'),
            ('node_1', 'node_2'),
            ('node_3', 'output'),
            ('input_2', 'node_4'),
            ('node_4', 'output'),
            ('input_3', 'output')
        ]
        graph = build_graph(nodes, edges)
        self.assertRaises(Error, add_input_ops, graph, inputs, True)

    # Tests for cases with input/output ports cutting
    def test_add_input_with_input_port_before_infer(self):
        shape = np.array([1, 2, 3, 4])
        inputs = {'conv_1': [{'shape': shape, 'in': 0}]}
        nodes = {
            'old_input': {'type': 'Identity', 'kind': 'op', 'op': 'Parameter'},
            'conv_1': {'type': 'Convolution', 'kind': 'op', 'op': 'NotPlaceholder'},
            'relu_1': {'type': 'ReLU', 'kind': 'op', 'op': 'NotPlaceholder'},
            'output': {'type': 'SoftMax', 'kind': 'op', 'op': 'NotPlaceholder'}
        }
        edges = [
            ('old_input', 'conv_1'),
            ('conv_1', 'relu_1'),
            ('relu_1', 'output')
        ]
        graph = build_graph(nodes, edges)
        add_input_ops(graph=graph, user_defined_inputs=inputs, before_infer=True)

        # Check that graph
        graph_ref = build_graph(nodes, edges, update_attributes={'old_input': {'shape': shape}})
        (flag, resp) = compare_graphs(graph, graph_ref, last_node='output')
        self.assertTrue(flag, resp)

        # also checks that new old_input was changed
        new_input = list(graph.in_edges('conv_1'))[0][0]
        self.assertFalse(graph.node['old_input']['is_input'])
        self.assertTrue(graph.node[new_input]['is_input'])
        self.assertTrue((new_input, 'conv_1') in graph.edges())
        self.assertTrue(('old_input', 'conv_1') not in graph.edges())

    def test_add_input_with_output_port_before_infer(self):
        shape = np.array([1, 2, 3, 4])
        inputs = {'conv_1': [{'shape': shape, 'out': 0}]}
        nodes = {
            'old_input': {'type': 'Identity', 'kind': 'op', 'op': 'Parameter'},
            'conv_1': {'type': 'Convolution', 'kind': 'op', 'op': 'NotPlaceholder'},
            'conv_2': {'type': 'Convolution', 'kind': 'op', 'op': 'NotPlaceholder'},
            'relu_1': {'type': 'ReLU', 'kind': 'op', 'op': 'NotPlaceholder'},
            'output': {'type': 'SoftMax', 'kind': 'op', 'op': 'NotPlaceholder'}
        }
        edges = [
            ('old_input', 'conv_1'),
            ('conv_1', 'relu_1'),
            ('conv_2', 'relu_1'),
            ('relu_1', 'output')
        ]
        graph = build_graph(nodes, edges)
        add_input_ops(graph=graph, user_defined_inputs=inputs, before_infer=True)

        graph_ref = build_graph(nodes_attrs={'new_input': {'kind': 'op', 'op': 'Parameter', 'shape': shape},
                                             **nodes},
                                edges=[('new_input', 'relu_1'),
                                       ('relu_1', 'output'),
                                       ('conv_2', 'relu_1'),
                                       ('old_input', 'conv_1'),],)
        # Check that new input is added right (with right ports !)
        (flag, resp) = compare_graphs(graph, graph_ref, last_node='output')
        self.assertTrue(flag, resp)

        # Check that other graph is not damaged
        (flag, resp) = compare_graphs(graph, graph_ref, last_node='conv_1')
        self.assertTrue(flag, resp)

        # Checks for new input and edges
        self.assertTrue('conv_1/placeholder_out_port_0' in graph.nodes())
        new_input = 'conv_1/placeholder_out_port_0'
        self.assertTrue(graph.node[new_input]['is_input'])
        self.assertTrue((new_input, 'relu_1') in graph.edges())
        self.assertTrue(('old_input', 'relu_1') not in graph.edges())

    def test_add_input_with_output_port_after_infer(self):
        shape = np.array([1, 2, 3, 4])
        inputs = {'conv_1': [{'shape': shape, 'out': 0}]}
        nodes = {
            'old_input': {'type': 'Parameter', 'kind': 'op', 'op': 'Parameter'},
            'inp_data' : {'kind': 'data', 'shape': shape + 1},
            'conv_1': {'type': 'Convolution', 'kind': 'op', 'op': 'NotPlaceholder'},
            'conv_data': {'kind': 'data', 'shape': shape, 'value': None},
            'relu_1': {'type': 'ReLU', 'kind': 'op', 'op': 'NotPlaceholder'},
        }
        edges = [
            ('old_input', 'inp_data'),
            ('inp_data', 'conv_1'),
            ('conv_1', 'conv_data'),
            ('conv_data', 'relu_1'),
        ]
        graph = build_graph(nodes, edges)
        add_input_ops(graph=graph, user_defined_inputs=inputs, before_infer=False)

        graph_ref = build_graph(nodes_attrs={'new_input': {'kind': 'op', 'op': 'Parameter', 'shape': shape},
                                             **nodes},
                                edges=[('old_input', 'inp_data'),
                                       ('inp_data', 'conv_1'),
                                       ('new_input', 'conv_data'),
                                       ('conv_data', 'relu_1'),
                                       ],)
        # Check that new input is added right (with right ports !)
        (flag, resp) = compare_graphs(graph, graph_ref, last_node='relu_1')
        self.assertTrue(flag, resp)

        # Check that other graph is not damaged
        (flag, resp) = compare_graphs(graph, graph_ref, last_node='conv_1')
        self.assertTrue(flag, resp)

        # Checks for new input and edges
        self.assertTrue('conv_1/placeholder_out_port_0' in graph.nodes())
        new_input = 'conv_1/placeholder_out_port_0'

        self.assertTrue(graph.node[new_input]['is_input'])
        self.assertTrue((new_input, 'conv_data') in graph.edges())
        self.assertTrue(('conv_1', 'conv_data') not in graph.edges())


@generator
class TestOutputCut(unittest.TestCase):
    # {'embeddings': [{'port': None}]}
    @generate({'C': [{'port': None}]}, {'C': [{'out': 0}]}, {'C': [{'out': 1}]})
    def test_output_port_cut(self, output):
        nodes = {'A': {'type': 'Identity', 'kind': 'op', 'op': 'Identity'},
                 'B': {'type': 'Identity', 'kind': 'op', 'op': 'Identity'},
                 'C': {'type': 'Identity', 'kind': 'op', 'op': 'Identity'},
                 'D': {'type': 'Identity', 'kind': 'op', 'op': 'Identity'},
                 'E': {'type': 'Identity', 'kind': 'op', 'op': 'Identity'},
                 }
        edges = [
            ('A', 'C', {'in': 0, 'out': 0}),
            ('B', 'C', {'in': 1, 'out': 0}),
            ('C', 'D', {'in': 0, 'out': 0}),
            ('C', 'E', {'in': 0, 'out': 1})
        ]
        graph = build_graph_with_edge_attrs(nodes, edges)
        sinks = add_output_ops(graph, output)
        graph.clean_up()
        self.assertEqual(len(Node(graph, 'C').out_nodes()), 1)
        self.assertEqual(len(Node(graph, 'C').in_nodes()), 2)

    @generate({'C': [{'in': 0}]}, {'C': [{'in': 1}]})
    def test_output_port_cut(self, output):
        nodes = {'A': {'op': 'Parameter', 'kind': 'op'},
                 'B': {'op': 'Parameter', 'kind': 'op'},
                 'C': {'type': 'Identity', 'kind': 'op', 'op': 'Identity'},
                 'D': {'type': 'Identity', 'kind': 'op', 'op': 'Identity'},
                 'E': {'type': 'Identity', 'kind': 'op', 'op': 'Identity'},
                 }
        edges = [
            ('A', 'C', {'in': 0, 'out': 0}),
            ('B', 'C', {'in': 1, 'out': 0}),
            ('C', 'D', {'in': 0, 'out': 0}),
            ('C', 'E', {'in': 0, 'out': 1})
        ]
        graph = build_graph_with_edge_attrs(nodes, edges)
        sinks = add_output_ops(graph, output)
        graph.clean_up()
        self.assertEqual(len(graph.nodes()), 2)


class TestUserDataRepack(unittest.TestCase):
    nodes = {'A': {'name': 'Aa', 'op': 'Parameter', 'kind': 'op'},
             'B': {'name': 'Bb', 'op': 'Parameter', 'kind': 'op'},
             'C': {'name': 'Cc', 'type': 'Identity', 'value': None, 'kind': 'op', 'op': 'Identity'},
             'D': {'name': 'Dd', 'type': 'Identity', 'value': None, 'kind': 'op', 'op': 'Identity'},
             'E': {'name': 'Ee', 'type': 'Identity', 'value': None, 'kind': 'op', 'op': 'Identity'},
             }
    edges = [
        ('A', 'C', {'in': 0, 'out': 0}),
        ('B', 'C', {'in': 1, 'out': 0}),
        ('C', 'D', {'in': 0, 'out': 0}),
        ('C', 'E', {'in': 0, 'out': 1})
    ]

    def test_input_user_data_repack_none(self):
        graph = build_graph(self.nodes, self.edges)
        input, freeze_placeholder = input_user_data_repack(graph, None, None)
        self.assertEqual(input, None)
        self.assertEqual(freeze_placeholder, None)

    def test_input_user_data_repack_names_to_ids_list(self):
        graph = build_graph(self.nodes, self.edges)
        input, freeze_placeholder = input_user_data_repack(graph, ['Aa', 'Bb'], None)
        self.assertDictEqual(input, {'A': [{'shape': None, 'port': None}], 'B': [{'shape': None, 'port': None}]})
        self.assertEqual(freeze_placeholder, None)

    def test_input_user_data_repack_names_ports_in_out(self):
        graph = build_graph(self.nodes, self.edges)
        input, freeze_placeholder = input_user_data_repack(graph, ['Aa:0', '1:Cc'], None)
        self.assertDictEqual(input, {'A': [{'shape': None, 'out': 0}], 'C': [{'shape': None, 'in': 1}]})
        self.assertEqual(freeze_placeholder, None)

    def test_input_user_data_repack_dict_with_shapes(self):
        graph = build_graph(self.nodes, self.edges)
        shape_1 = np.array([1, 160, 160, 3])
        shape_2 = np.array([1, 127, 127, 3])
        input, freeze_placeholder = input_user_data_repack(graph, {'Aa': shape_1, 'Bb': shape_2}, None)
        self.assertDictEqual(input, {'A': [{'shape': shape_1, 'port': None}], 'B': [{'shape': shape_2, 'port': None}]})
        self.assertEqual(freeze_placeholder, None)

    def test_input_user_data_repack_dict_with_shapes_and_ports(self):
        graph = build_graph(self.nodes, self.edges)
        shape_1 = np.array([1, 160, 160, 3])
        shape_2 = np.array([1, 127, 127, 3])
        input, freeze_placeholder = input_user_data_repack(graph, {'Aa:0': shape_1, 'Bb:0': shape_2}, None)
        self.assertDictEqual(input, {'A': [{'shape': shape_1, 'out': 0}], 'B': [{'shape': shape_2, 'out': 0}]})
        self.assertEqual(freeze_placeholder, None)

    def test_freeze_placeholder_and_input(self):
        graph = build_graph(self.nodes, self.edges)
        shape_1 = np.array([1, 160, 160, 3])
        input, freeze_placeholder = input_user_data_repack(graph, {'Aa:0': shape_1}, {'Bb': False})
        self.assertDictEqual(input, {'A': [{'shape': shape_1, 'out': 0}], 'B': [{'shape': None, 'port': None}]})
        self.assertEqual(freeze_placeholder, {'B': False})

    def test_error(self):
        graph = build_graph(self.nodes, self.edges)
        self.assertRaises(Error, input_user_data_repack, graph, np.array([1, 227, 227, 3]), None)

    def test_error_2(self):
        graph = build_graph(self.nodes, self.edges)
        self.assertRaises(Error, input_user_data_repack, graph, np.array([1, 227, 227, 3]), None)

    def test_error_3(self):
        graph = build_graph(self.nodes, self.edges)
        self.assertRaises(Error, input_user_data_repack, graph, ['Bcb'], None)

    def test_input_and_freeze(self):
        graph = build_graph(self.nodes, self.edges)
        shape_1 = np.array([1, 160, 160, 3])
        input, freeze_placeholder = input_user_data_repack(graph, shape_1, {'Bb': True})
        self.assertDictEqual(input, {'A': [{'shape': shape_1, 'port': None}], 'B': [{'shape': None, 'port': None}]})
        self.assertDictEqual(freeze_placeholder, {'B': True})

    def test_freeze_new_placeholder_1(self):
        # create a new placeholder Cc:0 by cutting output port with shape_2 = [5] and freeze a value [1.0 1.0 2.0 3.0 5.0]
        graph = build_graph(self.nodes, self.edges)
        shape_1 = np.array([1, 160, 160, 3])
        shape_2 = np.array([5])
        input, freeze_placeholder = input_user_data_repack(graph, {'Aa:0': shape_1, 'Cc:0' : shape_2}, {'Bb': False, 'Cc:0' : [1.0, 1.0, 2.0, 3.0, 5.0]})
        self.assertDictEqual(input, {'A' : [{'shape' : shape_1, 'out' : 0}], 'B' : [{'shape' : None, 'port' : None}], 'C' : [{'shape' : shape_2, 'out' : 0}]})
        self.assertEqual(freeze_placeholder, {'B' : False, 'C/placeholder_out_port_0' : [1.0, 1.0, 2.0, 3.0, 5.0]})

    def test_freeze_new_placeholder_2(self):
        # create a new placeholder Ee by cutting input port with shape_2 = [2, 2] and freeze a value [[1.0, 1.0], [2.0, 3.0]]
        graph = build_graph(self.nodes, self.edges)
        shape_1 = np.array([1, 160, 160, 3])
        shape_2 = np.array([2, 2])
        input, freeze_placeholder = input_user_data_repack(graph, {'Aa:0': shape_1, 'Ee' : shape_2}, {'Bb': False, 'Ee' : [[1.0, 1.0], [2.0, 3.0]]})
        self.assertDictEqual(input, {'A' : [{'shape' : shape_1, 'out' : 0}], 'B' : [{'shape' : None, 'port' : None}], 'E' : [{'shape' : shape_2, 'port' : None}]})
        self.assertEqual(freeze_placeholder, {'B' : False, 'E/placeholder_port_None' : [[1.0, 1.0], [2.0, 3.0]]})

    def test_freeze_new_placeholder_error(self):
        # shape is not specified for new placeholder Cc:0 with frozen value
        graph = build_graph(self.nodes, self.edges)
        shape_1 = np.array([1, 160, 160, 3])
        self.assertRaises(Error, input_user_data_repack, graph, {'Aa:0': shape_1}, {'Bb': False, 'Cc:0' : [1.0, 1.0, 2.0, 3.0, 5.0]})

    def test_output_user_data_repack(self):
        graph = build_graph(self.nodes, self.edges)
        output = output_user_data_repack(graph, ['Cc'])
        self.assertDictEqual(output, {'C': [{'port': None}]})

    def test_output_user_data_repack_ports(self):
        graph = build_graph(self.nodes, self.edges)
        output = output_user_data_repack(graph, ['Cc:1', '0:Cc'])
        self.assertDictEqual(output, {'C': [{'out': 1}, {'in': 0}]})

    def test_output_user_data_repack_none(self):
        graph = build_graph(self.nodes, self.edges)
        output = output_user_data_repack(graph, None)
        self.assertEqual(output, None)


class TestExtractPort(unittest.TestCase):
    def setUp(self) -> None:
        nodes = {
            'input_id': {'type': 'Parameter', 'kind': 'op', 'op': 'Parameter', 'name': '1input1:0'},
            'conv_id': {'type': 'Convolution', 'kind': 'op', 'op': 'NotPlaceholder', 'name': '1input1'},
            'relu_id': {'type': 'ReLU', 'kind': 'op', 'op': 'NotPlaceholder', 'name': 'relu'},
            'squeeze_id': {'type': 'Squeeze', 'kind': 'op', 'op': 'NotPlaceholder', 'name': 'relu:0'},
        }
        edges = [
            ('input_id', 'conv_id'),
            ('conv_id', 'relu_id'),
            ('relu_id', 'squeeze_id'),
        ]
        self.graph = build_graph(nodes, edges)

    def test_out_port(self):
        node_id, direction, port = get_node_id_with_ports(self.graph, '1input1:0:0')
        self.assertEqual(node_id, 'input_id')
        self.assertEqual(direction, 'out')
        self.assertEqual(port, 0)

    def test_in_port1(self):
        node_id, direction, port = get_node_id_with_ports(self.graph, '0:1input1')
        self.assertEqual(node_id, 'conv_id')
        self.assertEqual(direction, 'in')
        self.assertEqual(port, 0)

    def test_in_port2(self):
        node_id, direction, port = get_node_id_with_ports(self.graph, '0:relu:0')
        self.assertEqual(node_id, 'squeeze_id')
        self.assertEqual(direction, 'in')
        self.assertEqual(port, 0)

    def test_no_port1(self):
        node_id, direction, port = get_node_id_with_ports(self.graph, '1input1')
        self.assertEqual(node_id, 'conv_id')
        self.assertEqual(direction, 'port')
        self.assertEqual(port, None)

    def test_no_port2(self):
        self.assertRaises(Error, get_node_id_with_ports, self.graph, '1input1:0')

    def test_non_int(self):
        self.assertRaises(Error, get_node_id_with_ports, self.graph, 'port:1input1')

    def test_two_ports(self):
        self.assertRaises(Error, get_node_id_with_ports, self.graph, '0:1input1:1')

    def test_name_looks_like_port_number(self):
        nodes = {
            'input_id': {'type': 'Parameter', 'kind': 'op', 'op': 'Parameter', 'name': '0'},
            'conv_id': {'type': 'Convolution', 'kind': 'op', 'op': 'NotPlaceholder', 'name': '1'},
            'relu_id': {'type': 'ReLU', 'kind': 'op', 'op': 'NotPlaceholder', 'name': '2'},
        }
        edges = [
            ('input_id', 'conv_id'),
            ('conv_id', 'relu_id'),
        ]
        graph = build_graph(nodes, edges)
        node_id, direction, port = get_node_id_with_ports(graph, '0:2')
        self.assertEqual(node_id, 'relu_id')
        self.assertEqual(direction, 'in')
        self.assertEqual(port, 0)


class TestCaffePythonFrontExtractorOp(unittest.TestCase):
    def test_get_attrs(self):
        exp_attrs = {"test_attr_1": 12, "test_attr_2": "sdf sdf"}
        param_str = "'test_attr_1': 12, 'test_attr_2': 'sdf sdf'"
        attrs = CaffePythonFrontExtractorOp.get_attrs(FakePythonParam(FakeMultiParam({'param_str': param_str})))
        self.assertEqual(exp_attrs, attrs)
